Chi Liu AMD AmosLewis
AmosLewis
/ deberta_torch_small.mlir
Created
November 14, 2022 17:17
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| func.func @forward(%arg0: !torch.vtensor<[1,128],si64>) -> !torch.vtensor<[1,128,1],f32>{ | |
| %int1 = torch.constant.int 1 | |
| %int32 = torch.constant.int 32 | |
| %int128 = torch.constant.int 128 | |
| %float1.000000e00 = torch.constant.float 1.000000e+00 | |
| %0 = torch.vtensor.literal(dense<0.000000e+00> : tensor<2xf32>) : !torch.vtensor<[2],f32> | |
| %1 = torch.vtensor.literal(dense_resource<__elided__> : tensor<2x32xf32>) : !torch.vtensor<[2,32],f32> | |
| %2 = torch.vtensor.literal(dense_resource<__elided__> : tensor<32x32xf32>) : !torch.vtensor<[32,32],f32> | |
| %3 = torch.vtensor.literal(dense_resource<__elided__> : tensor<32x37xf32>) : !torch.vtensor<[32,37],f32> | |
| %4 = torch.vtensor.literal(dense_resource<__elided__> : tensor<37x32xf32>) : !torch.vtensor<[37,32],f32> |
AmosLewis
/ debert_torch_ir_print.txt
Created
November 15, 2022 17:42
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| ➜ SHARK git:(main) ✗ torch-mlir-opt -pass-pipeline='builtin.module(torch-backend-to-tosa-backend-pipeline)' /tmp/_lambda.mlir -mlir-print-ir-after-all -mlir-disable-threading --debug | |
| Args: /home/chi/src/ubuntu20/shark/torch-mlir/build/bin/torch-mlir-opt -pass-pipeline=builtin.module(torch-backend-to-tosa-backend-pipeline) /tmp/_lambda.mlir -mlir-print-ir-after-all -mlir-disable-threading --debug | |
| Load new dialect in Context builtin | |
| ImplicitTypeIDRegistry::lookupOrInsert(mlir::SubElementTypeInterface) | |
| ImplicitTypeIDRegistry::lookupOrInsert(mlir::ShapedType) | |
| ImplicitTypeIDRegistry::lookupOrInsert(mlir::MemRefLayoutAttrInterface) | |
| ImplicitTypeIDRegistry::lookupOrInsert(mlir::SubElementAttrInterface) | |
| ImplicitTypeIDRegistry::lookupOrInsert(mlir::ElementsAttr) | |
| ImplicitTypeIDRegistry::lookupOrInsert(mlir::TypedAttr) | |
| ImplicitTypeIDRegistry::lookupOrInsert(mlir::SymbolOpInterface) |
AmosLewis
/ gather.mlir
Created
November 17, 2022 22:08
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| func.func @torch.aten.gather(%arg0: !torch.vtensor<[12,128,512],f32>, %arg1: !torch.vtensor<[1,128,128],si64>) -> !torch.vtensor<[12,128,128],f32> { | |
| %int-1 = torch.constant.int -1 | |
| %false = torch.constant.bool false | |
| %0 = torch.aten.gather %arg0, %int-1, %arg1, %false : !torch.vtensor<[12,128,512],f32>, !torch.int, !torch.vtensor<[1,128,128],si64>, !torch.bool -> !torch.vtensor<[12,128,128],f32> | |
| return %0 : !torch.vtensor<[12,128,128],f32> | |
| } |
AmosLewis
/ gathernd.mlir
Created
December 5, 2022 06:54
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| func.func @torch.aten.gather(%arg0: !torch.vtensor<[1,4,3],f32>, %arg1: !torch.vtensor<[1,4,2,3],si64>) -> !torch.vtensor<[1,4,2],f32> { | |
| %int-1 = torch.constant.int -1 | |
| %false = torch.constant.bool false | |
| %0 = torch.aten.gather %arg0, %int-1, %arg1, %false : !torch.vtensor<[1,4,3],f32>, !torch.int, !torch.vtensor<[1,4,2,3],si64>, !torch.bool -> !torch.vtensor<[1,4,2],f32> | |
| return %0 : !torch.vtensor<[1,4,2],f32> | |
| } |
AmosLewis
/ gathernd_expand_algorithm_explanation.cpp
Last active
December 16, 2022 07:36
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| module { | |
| func.func @torch.aten.gather(%arg0: !torch.vtensor<[1,4,3],f32>, %arg1: !torch.vtensor<[1,4,2,3],i32>) -> !torch.vtensor<[1,4,2],f32> { | |
| %0 = torch_c.to_builtin_tensor %arg0 : !torch.vtensor<[1,4,3],f32> -> tensor<1x4x3xf32> | |
| %0= torch.tensor([[ | |
| [1, 2, 3], | |
| [4, 5, 6], | |
| [7, 8, 9], | |
| [10, 11, 12] | |
| ]]) # 1*4*3 | |
| %1 = torch_c.to_builtin_tensor %arg1 : !torch.vtensor<[1,4,2,3],i32> -> tensor<1x4x2x3xi32> |
AmosLewis
/ tosa_concat_example.txt
Last active
December 15, 2022 05:07
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| value1: | |
| vec:[0,0,0,0,0,0,0] | |
| shape: 1*4*2*1 | |
| tosa::getConstTensor | |
| tensor([[ | |
| [ | |
| [0], [0] | |
| ], | |
| [ | |
| [0], [0] |
AmosLewis
/ gathernd_torch.mlir
Created
December 15, 2022 21:30
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| func.func @torch.aten.gather(%arg0: !torch.vtensor<[1,4,3],f32>, %arg1: !torch.vtensor<[1,4,2],si64>) -> !torch.vtensor<[1,4,2],f32> { | |
| %int-1 = torch.constant.int -1 | |
| %false = torch.constant.bool false | |
| %0 = torch.aten.gather %arg0, %int-1, %arg1, %false : !torch.vtensor<[1,4,3],f32>, !torch.int, !torch.vtensor<[1,4,2],si64>, !torch.bool -> !torch.vtensor<[1,4,2],f32> | |
| return %0 : !torch.vtensor<[1,4,2],f32> | |
| } |
AmosLewis
/ gathernd_torch_deberta.mlir
Created
December 15, 2022 22:41
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| func.func @torch.aten.gather(%arg0: !torch.vtensor<[12,128,512],f32>, %arg1: !torch.vtensor<[1,128,128],si64>) -> !torch.vtensor<[12,128,128],f32> { | |
| %int-1 = torch.constant.int -1 | |
| %false = torch.constant.bool false | |
| %0 = torch.aten.gather %arg0, %int-1, %arg1, %false : !torch.vtensor<[12,128,512],f32>, !torch.int, !torch.vtensor<[1,128,128],si64>, !torch.bool -> !torch.vtensor<[12,128,128],f32> | |
| return %0 : !torch.vtensor<[12,128,128],f32> | |
| } |
AmosLewis
/ deberta_torch.mlir
Created
December 16, 2022 21:35
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| #loc = loc(unknown) | |
| module attributes {torch.debug_module_name = "_lambda"} { | |
| func.func @forward(%arg0: !torch.vtensor<[1,128],si64> loc(unknown)) -> !torch.vtensor<[1,2],f32> { | |
| %int0 = torch.constant.int 0 loc(#loc1) | |
| %int1 = torch.constant.int 1 loc(#loc2) | |
| %true = torch.constant.bool true loc(#loc3) | |
| %float1.000000e00 = torch.constant.float 1.000000e+00 loc(#loc3) | |
| %none = torch.constant.none loc(#loc) | |
| %int11 = torch.constant.int 11 loc(#loc4) | |
| %false = torch.constant.bool false loc(#loc5) |
AmosLewis
/ deberta_tosa_stateofart_fail.mlir
Created
December 16, 2022 21:37
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| ➜ deberta git:(main) ✗ torch-mlir-opt -pass-pipeline='builtin.module(torch-backend-to-tosa-backend-pipeline)' /tmp/_lambda.mlir --mlir-print-ir-after-failure -mlir-disable-threading | |
| <eval_with_key>.2:8:54: error: failed to legalize operation 'torch.constant.int' | |
| <eval_with_key>.2:8:54: note: see current operation: %1 = "torch.constant.int"() {value = 0 : i64} : () -> !torch.int | |
| // -----// IR Dump After FinalizingBackendTypeConversion Failed (torch-finalizing-backend-type-conversion) //----- // | |
| func.func @forward(%arg0: tensor<1x128xi64>) -> tensor<1x2xf32> { | |
| %0 = "tosa.const"() {value = dense<[[65536, 512, 1]]> : tensor<1x3xi32>} : () -> tensor<1x3xi32> | |
| %int0 = torch.constant.int 0 | |
| %1 = "tosa.const"() {value = dense_resource<__elided__> : tensor<2x768xf32>} : () -> tensor<2x768xf32> | |
| %2 = "tosa.const"() {value = dense_resource<__elided__> : tensor<768x768xf32>} : () -> tensor<768x768xf32> | |
| %3 = "tosa.const"() {value = dense_resource<__elided__> : tensor<768xf32>} : () -> tensor<768xf32> |